Identifying demand sources that minimize risk for a selective newsvendor
WSC '05 Proceedings of the 37th conference on Winter simulation
Market selection decisions for inventory models with price-sensitive demand
Journal of Global Optimization
Risk management in uncapacitated facility location models with random demands
Computers and Operations Research
Research on dynamic pricing model of electronic airplane ticket in electronic commerce
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Inverse problems and solution methods for a class of nonlinear complementarity problems
Computational Optimization and Applications
Dynamic Capacity Allocation to Customers Who Remember Past Service
Management Science
On capacity allocation for operating rooms
Computers and Operations Research
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The classical newsvendor problem is one of optimally choosing a level of capacity to respond to a known demand distribution. The inverse newsvendor problem is one of optimally choosing a demand distribution with fixed capacity. The applications of the inverse problem include industrial settings where demand management is relatively less costly than capacity adjustments. Demand distributions are chosen from an opportunity set, which reflects the set of market opportunities for the firm. We analyze the firm's profit as a function of these demand alternatives, provide solution methods and insights, and identify inefficient and dominated distributions. We provide results when the opportunity set is known or only partially known. We extend the results to cases in which there are multiple prioritized customer classes that share the firm's productive capacity. This paper was motivated by an industrial application in a firm selling a semicommodity product into three prioritized industrial sectors. We review the application of our methods to this setting.